Automated QA System Establishment via Dynamic Extraction Template Adjustment
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Solution Overview
Problem
Current question and answer (QA) systems are inefficient and prone to human errors due to manual establishment processes, leading to time-consuming and inaccurate information retrieval.
Innovation Solution
A method involving determining QA pair data using an extraction template and target data source, adjusting the template based on anomaly information, and updating the data to establish a QA system, thereby improving efficiency and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual processes (crawler program, indexing program) are used to establish QA system, then system establishment can be performed, but efficiency is low and human errors increase
Solution Approach 1:
The system automatically detects anomalies in QA pair data and self-adjusts the extraction template without human intervention. The anomaly detection module identifies issues in extracted data, and the system automatically modifies the extraction template to correct these anomalies, enabling self-service operation that eliminates human errors while maintaining high efficiency
Solution Approach 2:
The system implements a feedback mechanism where extracted QA pair data is evaluated for anomalies, and this feedback is used to automatically adjust the extraction template. The feedback loop continues until no anomalies are detected or a maximum number of adjustments is reached, ensuring high accuracy through iterative self-correction without manual intervention
2Reliability
If manual processes are used to establish QA system, then system can be created, but time consumption increases
Solution Approach 1:
The system performs preliminary anomaly detection on extracted QA pair data before finalizing the QA system establishment. By detecting and correcting anomalies in advance through automatic template adjustment, the system ensures data correctness without requiring time-consuming manual verification, thus reducing overall establishment time while maintaining high reliability
3Productivity
If automated extraction template is used, then establishment efficiency improves, but accuracy may decrease due to anomaly detection challenges
Solution Approach 1:
The extraction template is made dynamic and adjustable based on detected anomalies. The system automatically modifies template parameters such as extraction paths, node names, and regex patterns in response to anomaly detection results, allowing the template to adapt and improve its precision iteratively without reducing establishment efficiency
Solution Approach 2:
The system changes multiple parameters of the extraction template including extraction paths, node names, regular expressions, and selector expressions based on detected anomalies. By adjusting these parameters automatically, the system maintains high measurement precision in anomaly detection while preserving fast automated establishment efficiency
Data Source
AI summary
Methods, systems, and devices, including computer programs encoded on computer storage media, for establishing a question and answer (QA) system are provided. One of the methods includes: determining QA pair data according to an extraction template and a target data source; adjusting the extraction template according to anomaly information corresponding to the QA pair data; updating the QA pair data according to the target data source and the adjusted extraction template; and determining a QA index according to the updated QA pair data to establish a QA system.